principles and foundations of ontologies and semantic grids
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Principles and Foundations of Ontologies and Semantic Grids
Oscar CorchoUniversity of Manchester
International Summer School on Grid Computing 2006 (ISSGC 2006)Session 32. Wednesday, July 19th 2006
http://www.cs.man.ac.uk/~ocorcho/ISSGC2006/
Motivation
Organisations that manage large datasets have to find agreements on what terms mean
Data versus metadata: we need bindings between the data and the data structure
Well-typed workflows can be annotated with semantic typesKepler can use keyword-based or ontology-based search
Data, metadata an ontology (NSF report)
Making this change in the code would change the [implicit] semantics of this Globus service
Provenance in Taverna is stored in RDF and OWLWorkflow reuse
Motivation. Metadata Matters • Particularly for the following activities:
– Resource discovery – Provenance– Data integration– Systems Configuration– Policy representation and reconciliation
• Using:– Open, flexible and extensible self describing schemas that don’t have to be
nailed down• “Let’s describe my data set, or the output format of this tool”• Lightweight schemas• Decoupled, interoperable systems, which resist to syntactic changes
– Open world• “This metadata is no longer valid because...”
– Data integration across different data models (e.g. RDF)• Like policy or resource models
– Formalization & Reasoning support
Overview• Ontologies and the Semantic Web (45 minutes)
– Introduction– What is the Semantic Web
• Annotation, Integration, Inference– Semantic Web Technologies
• RDF, RDF Schema and OWL• Semantic Grid: History, Projects and Case Studies (15
minutes)– Semantic Grid History– Semantic Grid: Use Cases
• Semantic-OGSA (S-OGSA) (30 minutes)– S-OGSA Reference Model and Capabilities– S-OGSA Mechanisms and Interaction Patterns– A Sample Deployment of S-OGSA
• Credits
What is the Semantic Web• An extension of the current Web…
– … where information and services are given well-defined and explicitly represented meaning, …
– … so that it can be shared and used by humans and machines, ...
– ... better enabling them to work in cooperation
• How? – Promoting information exchange
by tagging web content with machine processable descriptions of its meaning.
– And technologies and infrastructure to do this
The Semantic Web Vision• The Web was made possible through established standards
– TCP/IP for transporting bits down a wire– HTTP & HTML for transporting and rendering hyperlinked text
• Applications able to exploit this common infrastructure– Result is the WWW as we know it
• Generations– 1st generation web mostly handwritten HTML pages– 2nd generation (current) web often machine generated/active
• Both intended for direct human processing/interaction– In the next generation web, resources should be more accessible to automated processes
• To be achieved via semantic markup• Metadata annotations that describe content/function
The Syntactic Web
The Semantic Web
Where we are Today: the Syntactic Web
Resource
ResourceResource Resource Resource
ResourceResource Resource
Resource
Resource
hrefhrefhref
hrefhrefhref
hrefhrefhref
href href
href
• A place where computers do the presentation (easy) and people do the linking and interpreting (hard).
• Why not get computers to do more of the hard work?
Hard Work using the Syntactic Web…
Find images of Oscar Corcho
…Malcolm Atkinson
… David Fergusson …
What’s the Problem?• Typical web page markup
consists of:• Rendering information
(e.g., font size and colour)• Hyper-links to related
content• Semantic content is accessible
to humans but not (easily) to computers…
Information we can see…International Summer School on Grid Computing (ISSGC2006)Ischia (Naples)July 9-21, 2006
Organisers/sponsors/... ?ICEAGE, GGF, EGEE
CurriculumStructured in two weeksSessions each day
Agenda for each daySession titleSession speakerSession descriptionSession slides and additional material
…
…
…
Information a machine can see…
Solution: XML markup with “meaningful” tags?
<name> </name><date> </date> <location> </location>
<introduction>
… </introduction><speaker> <bio> </bio></speaker><speaker> <bio> </bio></speaker> <registration>
<registration>
But What About…?
<conf> </conf><date> </date> <place> </place>
<introduction>
… </introduction><speaker> <bio> </bio></speaker><speaker> <bio> </bio></speaker> <registration>
<registration>
Still the Machine only sees…
< > < >< > </ > <> <>
< >
… </ >< > < > </ ></ >< > < > </ ></ > < >
< >
Need to Add “Semantics”• External agreement on meaning of annotations
– E.g., Dublin Core for annotation of library/bibliographic information• Agree on the meaning of a set of annotation tags
– Problems with this approach• Inflexible• Limited number of things can be expressed
• Use Ontologies to specify meaning of annotations– Ontologies provide a vocabulary of terms– New terms can be formed by combining existing ones
• “Conceptual Lego”– Meaning (semantics) of such terms is formally specified– Can also specify relationships between terms in multiple ontologies
Ontology in Computer Science• An ontology is an engineering artifact:
– It is constituted by a specific vocabulary used to describe a certain reality, plus
– a set of explicit assumptions regarding the intended meaning of the vocabulary.
• Almost always including concepts and their classification• Almost always including properties between concepts• Similar to an object oriented model
• Thus, an ontology describes a formal specification of a certain domain:– Shared understanding of a domain of interest– Formal and machine manipulable model of a domain of interest
Ontology Languages• Work on Semantic Web has concentrated on the definition of a
collection or “stack” of languages. – Used to support the representation and use of metadata– Basic machinery that we can use to represent the extra semantic
information needed for the Semantic Web
RDF(S)
Integrating information sources
Associating metadata to resources (bindings)
OWL
Integration
RDFS
RDF
XMLA
nnotation
Integration
Inference
Reasoning over the information we haveCould be light-weight (taxonomy)Could be heavy-weight (logic-style)
RDF• RDF stands for Resource Description Framework• It is a W3C Recommendation
– http://www.w3.org/RDF• RDF is a graphical formalism ( + XML syntax + semantics)
– for representing metadata– for describing the semantics of information in a machine- accessible
way• Provides a simple data model based on triples.
The RDF Data Model• Statements are <subject, predicate, object> triples:
– <Oscar,presents,Session32>• Can be represented as a graph:
• Statements describe properties of resources• A resource is any object that can be pointed to by a URI
– The generic set of all names/addresses that are short strings that refer to resources
– a document, a picture, a paragraph on the Web, http://www.cs.man.ac.uk/~ocorcho/index.html, a book in the library, a real person, isbn://0141184280
– Do not mistake them for Grid resources, though they could be the same, as we will see later in this talk!!
• Properties themselves are also resources (URIs)
Oscar Session32presents
Linking Statements• The subject of one statement can be the object of another• Such collections of statements form a directed, labeled graph
• The object of a triple can also be a “literal” (a string)
Oscar Session32presents
Pinar http://www.gs.unina.it/session-32.htm
preparedByhasHomePage
“Oscar Corcho”hasName
preparedBy
RDF Syntax• RDF has an XML syntax that has a specific meaning:• Every Description element describes a resource• Every attribute or nested element inside a Description is a property
of that Resource• We can refer to resources by URIs
<rdf:Description rdf:about="some.uri/person/ocorcho"> <o:presents rdf:resource="some.uri/session/Session32"/> <o:hasName rdf:datatype="&xsd;string">Oscar Corcho</o:hasName></rdf:Description><rdf:Description rdf:about="some.uri/session/Session32"> <o:hasHomePage>http://www.gs.unina.it/session-32.htm </o:hasHomePage> <o:preparedBy rdf:resource=“some.uri/person/ocorcho"> <o:preparedBy rdf:resource=“some.uri/person/pinar_alper"></rdf:Description>
What does RDF give us?• Single (simple) data model.• Syntactic consistency between names (URIs).
• A mechanism for annotating data and resources.• Low level integration of data.
OWLIntegration
RDFS
RDF
XML
Annotation
Integration
Inference
RDF(S)
What doesn’t RDF give us?• RDF does not give any special meaning to vocabulary
– Such as subClassOf or type (supporting OO-style modelling)
• So, what’s the difference between this graph...
• ... and this one?
Oscar Session32presents
“Oscar Corcho”hasName
preparedBy
Oscar Session32talksIn
“Oscar Corcho”isAlsoKnownAs
presentedBy
RDFS: RDF Schema• RDF Schema is another W3C Recommendation
– http://www.w3.org/TR/rdf-schema/• It extends RDF with a schema vocabulary that allows you to define
basic vocabulary terms and the relations between those terms– Class, type, subClassOf, – Property, subPropertyOf, range, domain– it gives “extra meaning” to particular RDF predicates and resources– this “extra meaning”, or semantics, specifies how a term should be
interpreted
• The combination of RDF and RDF Schema is normally known as RDF(S)
RDFS simple example<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xml:base="http://www.ontogrid.net/StickyNote#" xmlns="http://www.ontogrid.net/StickyNote#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"> <rdfs:Class rdf:ID="Event"> <rdfs:subClassOf rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> </rdfs:Class> <rdfs:Class rdf:ID="Local_Event"> <rdfs:subClassOf rdf:resource="#Event"/> </rdfs:Class> <rdfs:Class rdf:ID="Regional_Event"> <rdfs:subClassOf rdf:resource="#Event"/> </rdfs:Class> <rdfs:Class rdf:ID="Personal_Event"> <rdfs:subClassOf rdf:resource="#Event"/> </rdfs:Class> <rdfs:Class rdf:ID="Person"> <rdfs:subClassOf rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> </rdfs:Class> <rdfs:Class rdf:ID="Professor"> <rdfs:subClassOf rdf:resource="#Person"/> </rdfs:Class> <rdfs:Class rdf:ID="Researcher"> <rdfs:subClassOf rdf:resource="#Person"/> </rdfs:Class> <rdf:Property rdf:ID="involves">
<rdfs:domain rdf:resource="#Personal_Event"/> <rdfs:range rdf:resource="#Person"/>
</rdf:Property> <rdf:Property rdf:ID="eventDate">
<rdfs:domain rdf:resource="#Event"/> <rdfs:range rdf:resource="http://www.w3.org/2001/XMLSchema#date"/>
</rdf:Property></rdf:RDF>
Event
Personal_Event Local_Event Regional_Event
Person
Professor Researcher
subClassOf subClassOf
subClassOfsubClassOf
subClassOf
involves
xsd:dateeventDate
RDF(S) Inference
Lecturer
Academic
Person
rdfs:subClassOf
rdf:subClassOf
rdfs:subClassOf
rdf:type
rdfs:Classrdf:type
rdf:type
RDF(S) Inference
Oscar
Lecturer
rdf:type
rdfs:Class
Academic
rdfs:subClassOf
rdf:type
rdf:type
rdf:type
Seamark Demo:
ID new drug candidates for
BRKCB-1
GO2Keyword.rdf
UniProt.rdfGO.rdf
Keywords.rdf
Taxonomy.rdfPubMed.xml
Citation
IntAct.rdf
Organism
Enzymes.rdf
OMIM.rdf
GO2OMIM.rdf
GO2Enzyme.rdf
MIM Id
KEGG.rdf
KeywordGO2UniProt.rdf
Protein
Enzyme
ProbeSet.rdf
Gene
Probe
Pathway
Compound
Courtesy Joanne Luciano http://139.91.183.30:9090/RDF/VRP/Examples/schema_go.rdfhttp://139.91.183.30:9090/RDF/VRP/Examples/go.rdf
What does RDFS give us?• Ability to use simple schema/vocabularies to describe our resources• Consistent vocabulary use and sharing• Simple inference• Query mechanisms: SPARQL, SeRQL, RDQL, …
– SELECT N FROM {N} rdf:type {sti:Event} USING NAMESPACE sti=<http://www.ontogrid.net/StickyNote#>
• Examples– CS AktiveSpace
• Lightweight schema to integrate data from University sites
– myGrid• Service descriptions for e-Science
What doesn’t RDFS give us?• RDFS is too weak to describe resources in sufficient detail
– No localised range and domain constraints• Can’t say that the range of hasEducationalMaterial is Slides when
applied to TheoreticalSession and Code when applied to HandsonSession
– TheoreticalSession hasEducationalMaterial Slides– HandsonSession hasEducationalMaterial Code
– No existence/cardinality constraints• Can’t say:
– Sessions must have some EducationalMaterial– Sessions have at least one Presenter
– No transitive, inverse or symmetrical properties• Can’t say that presents is the inverse property of isPresentedBy
Joint EU/US Committee
DAML
OntoKnowledge+Others
The OWL Family Tree
Frames
Description Logics
RDF/RDF(S)
OIL
DAML-ONT
DAML+OIL OWLW3C
OWL• W3C Recommendation (February 2004) • A family of Languages
– OWL Full– OWL DL– OWL Lite
• Formal semantics– Description Logics (DL/Lite)– Relationship with RDF
OWL Basics (on top of RDF and RDFS)• Set of constructors for concept expressions
– Booleans: and/or/not• A Session is a TheoreticalSession or a HandsonSession• Slides are not the same as Code
– Quantification: some/all• Sessions must have some EducationalMaterial• Sessions can only have Presenters that have developed Grid
applications or Grid middleware
• Axioms for expressing constraints– Necessary and Sufficient conditions on classes
• A Session that hasEducationalMaterial Code is a HandsonSession.– Disjointness
• TheoreticalSessions are disjoint with HandsonSessions – Property characteristics: transitivity, inverse
phosphoglucoseisomerase 5.3.1.9
OWL(schema)
Instances (Individuals)
(data)
OWL Ontology ExampleBioPAX Biochemical Reaction
Courtesy Joanne
Luciano
K Wolstencroft, A Brass, I Horrocks, P. Lord, U Sattler, R Stevens, D Turi A little semantics goes a long way in Biology Proc 4th ISWC 2005
OWL Ontology Example. BioPAX ontology• http://www.biopax.org/release/biopax-level2.owl
Reasoning Tasks• OWL DL based on a well understood Description Logic (SHOIN(Dn))
– Formal properties well understood (complexity, decidability)– Known reasoning algorithms– Implemented systems (highly optimised)
• Because of this, we can reason about OWL ontologies– Subsumption reasoning
• Allows us to infer when one class is a subclass of another• Can then build concept hierarchies representing the taxonomy. • This is classification of classes.
– Satisfiability reasoning• Tells us when a concept is unsatisfiable
– i.e. when it is impossible to have instances of the class.• Allows us to check whether our model is consistent.
– Instance Retrieval/Instantiation• What are the instances of a particular class C?• What are the classes that x is an instance of?
Sean Bechhofer:
Concrete Examples: Grid/VO?
GONG?
Reasoning Tasks. Classification
What does OWL give us?• Ability to use complex schema/vocabularies to describe our
resources.• Consistent vocabulary use and sharing.• Robust data integration techniques• Complex inference and several reasoning functions• Query mechanisms: OWL QL
Overview• Ontologies and the Semantic Web (45 minutes)
– Introduction– What is the Semantic Web
• Annotation, Integration, Inference– Semantic Web Technologies
• RDF, RDF Schema and OWL• Semantic Grid: History, Projects and Case Studies (15
minutes)– Semantic Grid History– Semantic Grid: Use Cases
• Semantic-OGSA (S-OGSA) (30 minutes)– S-OGSA Reference Model and Capabilities– S-OGSA Mechanisms and Interaction Patterns– A Sample Deployment of S-OGSA
• Credits
“The Semantic Grid is an extension of the current Grid in which information and services are given well-defined and explicitly represented meaning, so that it can be shared and used by humans and machines, better enabling computers and people to work in cooperation” D. De Roure, et. al
The Semantic Grid
Semantics in and on the Grid
• Web Sites– www.semanticgrid.org– Setting up the www.semanticgridcafe.org
• GGF Semantic Grid Research Group (SEM-RG)– Mailing List: sem-grd@gridforum.org
CombeChem
Semantic Grid history
Time
Efforts
Implicit Semantics1st generation
SRBImplicit SemanticsOGSA generation
GGF Semantic Grid Research GroupMany workshops
Systematic Investigation Phase
Specific experimentsPart of the Architecture
Dagstuhl Schloss Seminar Grid Resource OntologyMany projects
Pioneering PhaseAd-hoc experiments, early
pioneers
SDK
Demonstration Phase
Semantic Grid: Use Cases• Semantic Grid for Annotation of Data
– Already seen before in the cases of BioPAX and Gene Ontology• Semantic Grid in Workflows
– Service description and discovery (myGrid)• Semantic Grid in Data Integration
– Data Integration (www.godatabase.org)– Data Integration (GEON)
• Semantic Grid in Authorisation– We will see an example later
myGrid: Workflow and Service Annotation
?
• Large # of services, 3000+
• No real description of capabilities
• A common abstraction “Processor”
• Users do the selection
myGrid: Workflow and Service Annotation
Registryplug-in
Taverna Workbench
Registry
PedroAnnotation tool
Ontology Store
Vocabulary
Others
WSDLSoap-
lab
ServiceProviders
Description extraction
Ontologists
Interface Description
Annotation/description
Annotation providers
myGrid: Workflow and Service Annotation
Registryplug-in
Taverna Workbench
Registry
PedroAnnotation tool
Ontology Store
Vocabulary
Others
WSDLSoap-
lab
ServiceProviders
Description extraction
Ontologists
Interface Description
Annotation/description
Annotation providers
myGrid: Workflow and Service Annotation
Registryplug-in
Taverna Workbench
Registry
PedroAnnotation tool
Ontology Store
Vocabulary
Others
WSDLSoap-
lab
ServiceProviders
Description extraction
Ontologists
Interface Description
Annotation/description
Annotation providers
myGrid: Workflow and Service Annotation
Registryplug-in
Taverna Workbench
Registry
PedroAnnotation tool
Ontology Store
Vocabulary
Others
WSDLSoap-
lab
ServiceProviders
Description extraction
Ontologists
Interface Description
Annotation/description
Annotation providers
myGrid: Workflow and Service Annotation• Word-based search
• Semantic annotation for later discovery and (re)use
– User chooses services/workflows• Unlike in Semantic Web
Services approaches– A common ontology is used to
annotate and query myGrid services/workflows
– In the example, we are looking for all workflows/services that accept an input of semantic type nucleotide sequence
Data Integration in GO
Gene Symbol FunctionASA1 tryptophan biosynthesis
Locus Name FunctionF15D2.31 tryptophan biosynthesis
www.godatabase.org
Courtesy Chris Wroe
SiO2 is an instance of class AnalyticalOxideConcentration and has all
information about the element S i
Planetary Material Ontology
CYBERINFRASTRUCTURE FOR THE GEOSCIENCES A.K.Sinha, Virginia Tech, 2005
Data Integration in GEON
Overview• Ontologies and the Semantic Web (45 minutes)
– Introduction– What is the Semantic Web
• Annotation, Integration, Inference– Semantic Web Technologies
• RDF, RDF Schema and OWL• Semantic Grid: History, Projects and Case Studies (15
minutes)– Semantic Grid History– Semantic Grid: Use Cases
• Semantic-OGSA (S-OGSA) (30 minutes)– S-OGSA Reference Model and Capabilities– S-OGSA Mechanisms and Interaction Patterns– A Sample Deployment of S-OGSA
• Credits
CombeChem
Semantic Grid history
Time
Efforts
Implicit Semantics1st generation
SRBImplicit SemanticsOGSA generation
GGF Semantic Grid Research GroupMany workshops
Systematic Investigation Phase
Specific experimentsPart of the Architecture
Dagstuhl Schloss Seminar Grid Resource OntologyMany projects
Pioneering PhaseAd-hoc experiments, early
pioneers
SDK
Demonstration Phase
From the pioneering phase to the systematic investigation phase
• In the pioneering phase...– Ontologies and their associated technologies are not completely
integrated in the Grid applications• They are used as in Semantic Web applications
– But there are distinctive features of Grid applications• Distribution of resources• Scale• Resource management and state• ... (non exhaustive and non compulsory list)
• In the systematic investigation phase– We have to take these features into account– And incorporate semantics as another Grid resource
– Our proposal is: S-OGSA
Introduction. Semantic-OGSA• Semantic-OGSA (S-OGSA) is...
– Our proposed Semantic Grid reference architecture– A low-impact extension of OGSA
• Mixed ecosystem of Grid and Semantic Grid services– Services ignorant of semantics– Services aware of semantics but unable to process them– Services aware of semantics and able to process (part of) them
• Everything is OGSA compliant
– Defined by • Information model
– New entities• Capabilites
– New functionalities• Mechanisms
– How it is delivered
Model
Capabilities Mechanisms
provide/consume
expose
use
S-OGSA Model
METADATAas SemanticAnnotations
S-OGSA Model Example
S-OGSA Model. Grid Entities• We can attach Semantic Bindings to anything
– People, meetings, discussions, conference talks– Scientific publications, recommendations, quality comments– Events, notifications, logs– Services and resources– Schemas and catalogue entries – Models, codes, builds, workflows, – Data files and data streams– Sensors and sensor data …
• To make it more useful, we should agree on– Controlled vocabularies / Ontologies
• Resource description models• Grid Resource Ontologies (work in progress)• Application domain vocabularies
Optimization
Execution Management
Resourcemanagement
Data
Security
Information Management
Infrastructure Services
Application 1 Application N O
GS
AS
eman
tic-O
GS
A
Semantic Provisioning
Services
S-OGSA Capabilities
Ontology
ReasoningKno
wle
dge Metadata
Annotation
Sem
antic
bin
ding
Semantic Provisioning Services
OntoKit: An implementation of S-OGSA
OntoKit: An implementation of S-OGSA
OntologyRole-based
AuthZ
Semantically Aware
S-OGSA Mechanisms. Patterns
Lifetime
MetadataService
Service
ResourceMetadataSeekingClient
Properties
Others….
Access/Query MetadataRefers to
Resource properties
OntologyService
A semantic ignorant service
S-OGSA Mechanisms. Patterns
Lifetime
MetadataService
OntologyService
Service
ResourceMetadataSeekingClient
Properties
Others…
Access/Query Semantic Bindings
Refers to
Get Semantic Binding Pointers
2
1Resource
properties
A semantic aware service, but incapable of processing semantics
S-OGSA Mechanisms. Patterns
Lifetime
MetadataService
Service
ResourceMetadataSeekingClient
Properties
Others…
Access/Query Semantic Bindings1Semantics
1.1
Farm out request
OntologyService
A semantic aware service, capable of processing semantics
A simple Authorisation Scenario • A role-based Access Control Scenario in the insurance domain.
• What?– Role based Access Control Policy is:
• “Good Reputation Drivers are allowed to ask for an insurance policy. Bad Reputation ones are not.”
• How?– VO ontology based on
• KaOS ontologies (Actors, Groups and Actions)– Role definitions
• Extend ontology with domain-specific classes and properties• Define roles wrt these extensions
– E.g., a blacklistedDriver is a driver that has had at least 3 accident claims in the past
– E.g., a goodReputationDriver is a driver that has been insured at least by one trusted company and that has had at most 2 accident claims
– The Access Control Function uses an OWL classifier to obtain roles of a Subject.
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
/C=GB/O=PERMIS/CN=User0
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
45
6
7
Atlas
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
Ignorant of semantics
Semantic aware and capable of processing semantics
Semantic provisioning services
Semantic aware but incapable of processing semantics
Credits• This tutorial is based on contributions from many authors. I hope to
acknowledge all of them...– Sean Bechhofer, Carole Goble and David de Roure
• Section “Ontologies and the Semantic Web”, based on Semantic Grid 101 presented at GGF16 in February 2006
– The OntoGrid team @ Manchester: Pinar Alper, Ioannis Kotsiopoulos, Paolo Missier, Sean Bechhofer, Carole Goble
• S-OGSA work– Many others whose names appear on the slides
• This tutorial has been funded in part by the European Commission, under the projects OntoGrid and RSSGRID
• Questions regarding this tutorial should be directed to– Oscar Corcho: Oscar (dot) Corcho at manchester (dot) ac (dot) uk
More information• Publications
– An overview of S-OGSA: a Reference Semantic Grid Architecture. Corcho O, Alper P, Kotsiopoulos I, Missier P, Bechhofer S, Goble C. Journal of Web Semantics 4(2):102-115. June 2006
• Source code– http://www.ontogrid.net/, For Downloading Distributions– Access to CVS
Connection type: pserveruser: ontogridpassword: not neededHost: rpc262.cs.man.ac.ukPort: 2401Repository path: /local/ontogrid/cvsrootmodule: prototype
Principles and Foundations of Ontologies and Semantic Grids
Oscar CorchoUniversity of Manchester
International Summer School on Grid Computing 2006 (ISSGC 2006)Session 32. Wednesday, July 19th 2006
Other slides: WS-DAIOnt-RDF(S)
For further information...
OGSA ‘Semantic’ limitations • No Grid compliant ontology access mechanisms in RDF(S) and
OWL
• No specialized registry for localizing ontologies
• No Grid compliant instance access mechanisms in RDF
• SemGrid Applications access ontologies as on the Semantic Web
Node A
RDF(S)
3store
Node C
OWL
Jena
Node B
RDF(S)
Kowaki
Node D
Ontology evaluatorOntology evaluator
Evaluating ontology...
Parameters Ontology1.rdf Ontology1.owl
File Edit Evaluation
<service> <name>robes</name> <atribute> <atrname>product</atrname> <value>dressingGown</value> </atribute> <atribute> <atrname>washing_instruction</atrname> <value>machineWash</value> <value>handWash</value> <value>dryClean</value> </atribute> </service>
OWL
Sesame
WebODE
What is WS-DAIOnt?
• Web Services Data Access and Integration – The Ontology Realization• Specification of Grid Compliant Ontology Services, which
– Defines a framework for creating ontology access services in a Grid environment
– Is fully compliant with S-OGSA (consequently with OGSA)
– Is based on up-to-date Grid standards (GGF)• WS-DAI
– Is based on Web Service standards (OASIS, W3C)• WS-RF, WS-Addressing...
• First implementation focused on RDF(S): WS-DAIOnt-RDF(S) – Sesame and Jena (Oracle RDF-store, Atlas)– Query languages: SPARQL, SeRQL, RDQL, RQL
WS-DAIOnt-RDF(S) Implementation Architecture
• Two-tier architecture
– Web Service tier
• Upper service layer
• Intermediate service layer
• Lower service layer
– RDF(S) access tier
• RDFSConnector
• Storage layer
Sesame
RDFSConnector
Upper service layer
Intermadiate service layer
Lowerservice layer
Storage layer
RDFSRepositorySelectorService
RDFSRepositoryService
RDFSClassService
Web Service Tier
RD
F(S) Access
Tier
Sesame
RDFSConnector
Upper service layer
Intermadiate service layer
Lowerservice layer
Storage layer
RDFSRepositorySelectorService
RDFSRepositoryService
RDFSClassService
Web
Ser
vice
Tie
rR
DF(
S) A
cces
sTi
erImplementation and Specification
RDFSRepositorySelector Service
RDFSRepositorySelectorAccess
RDFSRepositorySelectorFactory
RDFSRepositorySelectorDescription
RDFSRepository Service
RDFSRepositoryAccess
RDFSRepositoryFactory
RDFSRepositoryDescription
RDFSClass Service
RDFSClassAccess
RDFSClassDescription
RepositorySelectorService
RepositoryService
ResourceService
ListService
ContainerService
StatementService
PropertyService
ClassService
AltService
Web Service
Implem
entation Layer
WS-DAIOnt-RDF(S) Implementation
Where we are moving to…
Upper interface tier
Medium interface tier
Lower interface tier
WS-DAIOnt-RDF(S) Specification
RepositorySelectorAccess
RepositorySelectorFactory
RepositoryAccess
RepositoryAccessFactory
ResourceAccess
ListAccess
ContainerAccess
StatementAccess
PropertyAccess
ClassAccess
AltAccess
ContainerFactory
ContainerIteratorAccess
RDFSConnector
RD
F(S) StorageIm
plementation Layer
Sesame RDF Storage
SesameConnector
Jena RDF Storage
JenaConnector
OracleRDF Storage
OracleConnector . . .
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